Public Member Functions
	__init__ (self, std=1.0, correlation_length=1.0, white_noise=0.0, mean=0.0)

	fit (self, x_train, y_train)

	predict (self, x_predict)

Public Attributes
	std = std

	correlation_length = correlation_length

float	white_noise = white_noise

	mean = mean

	gp

Detailed Description

Gaussian Process Treegp class for Gaussian Process interpolation.

The basic GP regression, which uses Cholesky decomposition.

Parameters:
-----------
std : `float`, optional
    Standard deviation of the Gaussian Process kernel. Default is 1.0.
correlation_length : `float`, optional
    Correlation length of the Gaussian Process kernel. Default is 1.0.
white_noise : `float`, optional
    White noise level of the Gaussian Process. Default is 0.0.
mean : `float`, optional
    Mean value of the Gaussian Process. Default is 0.0.

Definition at line 95 of file gp_interpolation.py.

Constructor & Destructor Documentation

◆ init()

lsst.meas.algorithms.gp_interpolation.GaussianProcessTreegp.__init__	(	self,
		std = 1.0,
		correlation_length = 1.0,
		white_noise = 0.0,
		mean = 0.0 )

Definition at line 113 of file gp_interpolation.py.

Member Function Documentation

◆ fit()

lsst.meas.algorithms.gp_interpolation.GaussianProcessTreegp.fit	(	self,
		x_train,
		y_train )

Fit the Gaussian Process to the given training data.

Parameters:
-----------
x_train : `np.array`
    Input features for the training data.
y_train : `np.array`
    Target values for the training data.

Definition at line 129 of file gp_interpolation.py.

◆ predict()

lsst.meas.algorithms.gp_interpolation.GaussianProcessTreegp.predict	(		self,
			x_predict )

Predict the target values for the given input features.

Parameters:
-----------
x_predict : `np.array`
    Input features for the prediction.

Returns:
--------
y_pred : `np.array`
    Predicted target values.

Definition at line 150 of file gp_interpolation.py.

Member Data Documentation

◆ correlation_length

lsst.meas.algorithms.gp_interpolation.GaussianProcessTreegp.correlation_length = correlation_length

Definition at line 115 of file gp_interpolation.py.

◆ gp

lsst.meas.algorithms.gp_interpolation.GaussianProcessTreegp.gp

Initial value:

=  treegp.GPInterpolation(
            kernel=kernel,
            optimizer="none",
            normalize=False,
            white_noise=self.white_noise,
        )

Definition at line 141 of file gp_interpolation.py.

◆ mean

lsst.meas.algorithms.gp_interpolation.GaussianProcessTreegp.mean = mean

Definition at line 117 of file gp_interpolation.py.

◆ std

lsst.meas.algorithms.gp_interpolation.GaussianProcessTreegp.std = std

Definition at line 114 of file gp_interpolation.py.

◆ white_noise

float lsst.meas.algorithms.gp_interpolation.GaussianProcessTreegp.white_noise = white_noise

Definition at line 116 of file gp_interpolation.py.

The documentation for this class was generated from the following file:

python/lsst/meas/algorithms/gp_interpolation.py

Public Member Functions

Public Attributes